Bio-Mimetic Approaches in Management Science: 1 (Advances in Computational Management Science, 1) - Hardcover

Hardcover

ISBN 10: 0792349938 ISBN 13: 9780792349938

Publisher: Springer, 1998

Synopsis

Management Science is often confronted with optimization problems characterised by weak underlying theoretical models and complex constraints. Among them, one finds data analysis, pattern recognition (classification, multidimensional analysis, discriminant analysis) as well as modelling (forecasting, confirmatory analysis, expert system design). In recent years, biomimetic approaches have received growing attention from Marketing, Finance and Human Resource researchers and executives as effective tools for practically handling such problems. Biomimetic approaches include a variety of heuristic methods - such as neural networks, genetic algorithms, immunitary nets, cellular automata - that simulate nature's way of solving complex problems and, thus, can be considered as numerical transpositions of true life problem solving.
Bio-Mimetic Approaches in Management Science presents a selection of recent papers on biomimetic approaches and their application to Management Science. Most of these papers were presented at the last ACSEG/CAEMS International Congresses (Approches Connexionnistes en Sciences Economiques et de Gestion/Connectionnist Approaches in Economics and Management Science). All papers combine the discussion of conceptual issues with illustrative empirical applications, and contain detailed information on the way heuristics are practically implemented. The advantages and limits of the biomimetic approaches are discussed in several of the papers, either by comparing these approaches with more classical methods (logit models, clustering), or by investigating specific issues like overfitting and robustness. Synthesizing overviews are provided, as well as new tools for coping with some of the limitations of biomimetic methods.

About this title

Synopsis

Management science is often confronted with optimization problems characterized by weak underlying theoretical models and complex constraints. Among them, one finds data analysis, pattern recognition (classification, multidimensional analysis, discriminant analysis) as well as modelling (forecasting, confirmatory analysis, expert system design). In recent years, bio-mimetic approaches have received growing attention from marketing, finance and human resource researchers and executives as effective tools for practically handling such problems. Bio-mimetic approaches include a variety of heuristic methods - such as neural networks, genetic algorithms, immunitary nets, cellular automata - that simulate nature's way of solving complex problems and, thus, can be considered as numerical transpositions of true life problem solving. This text presents a selection of papers on bio-mimetic approaches and their application to management science. Most of these papers were presented at an ACSEG/CAEMS International Congress (Approches Connexionnistes en Sciences Economiques et de Gestion/Connectionnist Approaches in Economics and Management Science).

All papers combine the discussion of conceptual issues with illustrative empirical applications, and contain detailed information on the way heuristics are practically implemented. The advantages and limits of the bio-mimetic approaches are discussed in several of the papers, either by comparing these approaches with more classical methods (logit models, clustering), or by investigating specific issues like overfitting and robustness. Synthesizing overviews are provided, as well as tools for coping with some of the limitations of bio-mimetic methods.

Edition details

• Publisher: Springer
• Publication date: 1998
• Language: English
• ISBN 10: 0792349938
• ISBN 13: 9780792349938
• Binding: Hardcover
• Number of pages: 218
• Editor: Aurifeille Jacques-Marie, Deissenberg Christopher